AWS, Microsoft unveil new deep learning framework for developers

Microsoft and Amazon Web Services have announced a new deep learning library that makes it easier for developers to get started with machine learning. Called Gluon, the interface offers built-in components that can be connected to form neural networks.

Simple and concise

Microsoft and Amazon might be fierce rivals in the cloud space but the two companies have a history in working together at the edges of research. Today's announcement is one such project, with both firms pooling their resources to push the boundaries of machine learning development.

Gluon is meant to lower the learning curve for developers getting started with neural networks. Aimed at programmers "of all skill levels," it enables new machine learning models to be created with "simple, concise" Python code.

This gives developers an interface to the AI that's easier to understand, letting them focus on designing the model. It's then implemented using code structures similar to the ones used in app and website development.

Optimising the process

Microsoft and Amazon said Gluon addresses one of the biggest trade-offs in neural network creation. New models have to be trained with large datasets, a process which can take days or weeks to complete.

To get around this, some deep learning engines like Microsoft's Cognitive Toolkit and Google's TensorFlow offer training optimisations to improve performance. However, these tend to complicate the code that defines how the model operates. Conversely, some engines focus on offering simpler model building at the expense of training performance.

Gluon shoots down the middle, offering developers a way to create neural networks on demand and then dynamically alter them. By combining the neural network model with its training algorithms, Gluon lets developers train their models in a step-by-step process. The end product is a powerful deep learning interface that's both accessible and performant.

Cutting out the "heavy lifting"

"The potential of machine learning can only be realized if it is accessible to all developers. Today's reality is that building and training machine learning models require a great deal of heavy lifting and specialized expertise," said Swami Sivasubramanian, vice president of Amazon AI. "We created the Gluon interface so building neural networks and training models can be as easy as building an app."

Gluon currently works with the Apache MXNet deep learning engine. Support for Microsoft's Cognitive Toolkit will be added in a future release. Both Amazon and Microsoft said they will continue to collaborate on Gluon, presenting it as a way of creating an "open AI ecosystem" that's accessible to the entire industry.

First, more deep learning providers will need to add support for Gluon, letting developers decide which AI toolchain to use. Integrating with Apache MXNet and Microsoft Cognitive Services is a start but for now teams using architecture from Google or Amazon are unable to access Gluon's benefits.